In-field device for de-centralized workflow automation

ABSTRACT

In one example, a system is provided. The system includes a portable, in-field unit including: a tag reader to acquire an ID tag identifier from a tag located in or on a physical item positioned within functional range of the in-field unit tag reader; a digital processor arranged for executing software code stored in the in-field unit responsive to the acquired ID tag identifier, the stored software code including—a customer application layer; and a database adapter component configured to provide database services to the processor; wherein the database services include accessing a stored database to acquire stored data associated with the acquired ID tag identifier.

PRIORITY

This application is a non-provisional of U.S. Provisional ApplicationNo. 61/543,243 filed on Oct. 4, 2011, entitled: MOBILE AND KIOSK DEVICESFOR DE-CENTRALIZED WORKFLOW AUTOMATION and, U.S. Provisional ApplicationNo. 61/543,264 filed on Oct. 4, 2011, entitled: MOBILE ELECTRONIC DATACAPTURE AND RECOGNITION, each of which are incorporated by referenceherein in their entirety.

BACKGROUND

Many courier, express, and Postal (“CEP”) companies rely on electronicdata interchange to capture and link unique barcodes with customerdestination addresses in order to automate their track & trace andsortation systems which are required for operational efficiency andon-time delivery commitments. Electronic data interchange (EDI) is thestructured transmission of data between organizations by electronicmeans. It is used to transfer electronic documents or business data fromone computer system to another computer system.

For many CEP companies, there is an ongoing challenge to capture andlink this vital information prior to collection and induction of parcelsinto their network. According to a Gartner study published in 2009,fewer than 25% of the total number of transportation/delivery companieshad implemented some level of automated EDI capture. And of thosecompanies, the range of EDI information available at induction can varybetween 50% to 99%. This current situation has a huge impact on dailyoperational cost and can negatively impact customer service because manyof these non-automated parcels where EDI information is missing requiresmanual processing which can impact delivery timelines. FIG. 1 representsa typical CEP workflow which illustrates both automated and manualprocesses.

Currently, all parcels that are missing critical EDI data must bererouted from an automated sortation system for manual processing.Manual processing of these parcels can take anywhere from 10 seconds, to10 minutes per parcel. For example: Assuming it would take a person 5minutes on average to manually link EDI information on a parcel, and thedepot received 300 parcels that require manual processing within a 4hour window, the carrier would have to assign 7 people to manuallyprocess all 300 parcels for next day delivery.

SUMMARY OF THE INVENTION

Embodiments of the present disclosure provide an unprecedentedopportunity for courier, express, and Postal (“CEP”) companies toincrease successful automated EDI rates by automatically linking missingbarcode and destination addresses data. Utilizing mobile OCR technologywith intelligent directory services, a parcel address label can beprocessed at the sender location (e.g. scanned by a ruggedized mobilecomputer and the address data is then extracted and verified on thehandset.) This local extraction and verification process provides thefollowing benefits:

-   -   Address and barcode data can be read instantaneously in one        simple scan transaction    -   Address errors automatically detected and corrected    -   Provides customized outputs from multiple data sources (e.g. add        GPS coordinates to the address data)    -   No over the air (OTA) network connection is required to process        a transaction

In one scenario the disclosure may be applied in an in-field device,e.g. a portable, mobile unit to be carried by an agent who picks upparcels in the field, and collects them for delivery to an originating“plant” for processing and routing toward their destination. Key datamay be acquired before the parcels even reach the plant.

In another scenario, parcels received at a plant (or receiving depot)may be processed by an agent using a similar in-field device. Using anembodiment of the disclosure, one operator could process on the order of300 parcels in less than 2 hours. Then the parcels are dispatched towardthe destination, with destination addresses already confirmed.

The economic benefit from this new technology is significant forcarriers. In addition to providing benefit in the CEP industry, in-fieldcapture and recognition of destination related data can also be appliedfor applications in warehousing, transportation, field service, andGovernment. Example use cases include reading and verifying licenseplates, Driver's license, Passports, identification cards, manufactureservice tags, parts, and other types of forms processing such asinvoices used for Bill of lading or CN-22 customs forms.

Additional aspects and advantages of this invention will be apparentfrom the following detailed description of preferred embodiments, whichproceeds with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a prior art address verification and deliveryprocess.

FIG. 2 is a simplified block diagram of an illustrative mobile softwarecomponent stack.

FIG. 3 is a simplified diagram of one example of a system in accordancewith the disclosure.

FIG. 4 is a simplified example of a flow diagram illustrating operationof an in-field device.

FIG. 5 is a flow diagram that illustrates the concept of the mobiledevice conducting recognition of digital image data using nativeresources, over a WiFi link, or via a wireless telecom networkconnection to a recognition system interface on a remote server.

DETAILED DESCRIPTION

The primary idea is to take existing technology (such as RAF Technology,Inc.'s address recognition products and capabilities), merge it within-field decentralized capture technology, e.g. mobile or kiosk-baseddecentralized capture technology, and create a more natural, optimizedprocess flow by doing so. If you transport a package to a central hubjust so you can read its address and induct the package into thetransshipment process, you have changed its normal flow (from origin todestination) solely to allow “automation” of the process. If, on theother hand, you capture the information in the field at, say, the pointof pickup of the package, you capture the same data, automate the sameprocess, but do it in a way that does not change the natural movement ofthe object.

A major concept in this document is that injecting automation (in-fielddevices such as mobile or other devices including kiosk devices) into awork flow without requiring change to that work flow (though it mayenable its optimization) enables the less technologically savvy to usetechnology in an appropriate place in the process, without having tounderstand how the technology works or even how the process proceeds. Bymerging capture technology (e.g. OCR, RFID, etc.) with mobility, we areputting information at humans' fingertips exactly where it is firstneeded in the process. This has two consequences. First, it enablesmachines to augment a human-centric process rather than the other wayaround.

Particularly in the first improvement described below, there exists amanual process (which may be part of a larger process that is manual orpartially automated) that has a flow that is natural to the way humanswork. We enable that human-centric processing flow to be maintained andoptimized by adding technology at an appropriate point (usually as earlyas possible in the process). The addition of the technology may allowoptimization of the human-centric flow, but does not requiremodification of that flow away from its human-centric origins.

Thus, for example, being able to take a package and determine it is tobe delivered to the office next door can be done by the courier readingthe delivery address (so he can then deliver the package next doorwithout taking it first to a centralized point). But it can be done moreeasily (and enhance the human courier's brain by “knowing” a wider rangeof “next door” addresses) if done at the point of pickup by a mobiledevice used to read the address and determine whether it is “local”.

The opposite of this—humans augmenting a machine process—would be, forexample, video encoding when a mail piece address cannot be read by theOCR machine. Thus in this case the only reason a human is in the processat all is to aid and backup the “automated” machine process when itfails. What we are proposing is the opposite—extending the ways amachine can support a human-centric process without requiring theirmodification.

The second consequence of putting information-collecting technology asearly as possible in the process flow (through the combination ofmobile/kiosk devices and our capture technology) is making more parts ofthe process accessible to optimization. Thus if a package's size,weight, and destination are captured when a courier picks up thepackage, the down-stream process typically has upwards of half a day(before the package makes it back to the routing hub) to optimallydetermine which truck/train/airplane the package should go on, takinginto account the size, weight, and destination of the package. Thatoptimal routing can begin immediately.

The Data Capture Automation Enhancement (discussed below) and theOptimal Location of Process Components Enhancement (discussed below) aremeant to be used in the increasingly important self-service industry(where people handle for themselves processes that were formerlycentralized), but they are not limited to those industries.

Data Capture Automation Enhancement

This concept combines mobile capture technology (hardware) withrecognition/authentication/verification technology (software) to takethe capture process to the object whose data is being captured ratherthan to have to take the object to the process. This operates in twoseparate, but related ways. First it takes a manual process that has anatural flow to it and, by injecting capture technology into the processas early as possible, enables the automation and possible optimizationof the process without requiring a fundamental change in the processflow.

Second, it enables the restoration of an already-automated process toits natural flow when the flow required to automate the process has beendiscordant with the natural flow of the process. The changes enabled bythis concept enable three things: the process remains automated, theautomation moves further upstream, and the process can be optimizedbetter as a result.

In some embodiments, the change enabled by our combining of mobilehardware capture with recognition/authentication/verification software,results in a process that no longer requires aggregation at a centralpoint where the aggregation was solely required by the automationprocess. In other words, there exists a natural manual process flow.That flow historically was disrupted and changed, sometimes drastically,by the requirements of the automation. That automation, nevertheless,gives sufficient benefit that the resulting automated process is nowmore efficient than the original manual one. The present concept allowsa restoration of the natural flow of the process while keeping orextending the automation of the process, allowing automation to proceedfurther upstream, and also to allow further optimization of thenow-restructured process.

When centralized aggregation of processed items was solely required bythe automation process (e.g. giant machines for “reading” and routingmail pieces were located at a central hub and the mail had to be takenthere to be processed), our concept allows the natural flow of thatprocess to be restored. In other words, there exists a natural manualprocess flow. Put another way, our concept allows one to separateprocess automation from process optimization and allows both to takeplace independently and optimally.

In particular, this concept enables the transformation of ahub-and-spoke process into a linear or a mesh process where the latterare more natural for the process. The routing of a package from point ofpickup to a delivery point “next door” (discussed above) is an exampleof this. By capturing the delivery information at the point of pickup,it is no longer necessary to take the package to a central hub for thatprocessing, only to have to bring it right back again. These changes canrealize huge gains in reducing delay and expense, and energy savings.

Optimal Location of Process Components

In some embodiments, providing a mobile capture device with access torecognition and other software, enables a process that has multiplecomponents required for carrying out one or several tasks. Some parts ofthat process are natural for doing at a particular place in the flow(e.g. where you read an identifier tag, such as an RFID tag, in thefield or where a person drops off a package at a kiosk, the naturalplace for data capture is in the field), while other parts of theprocess are more naturally located elsewhere (e.g. a centralizeddatabase containing information on RFID tags).

In the following section, we discuss a “back-end” (i.e., not “in thefield”) database but by “database” we mean any process that is remotefrom the in-field device. Our concept covers the separation of processcomponents that naturally occur in the field from process componentsthat take place in one or more additional locations. It does so in twodifferent ways, which can overlap:

-   -   a. Our concept, in an embodiment, envisions processing an object        in a cascade process of two or more steps. The first step        involves an “in the field” capture of data about the object and        the second (and possible additional) processes transmits the        information so collected to a database (or databases) that        cannot be localized at the capture point and hence must be        located elsewhere.    -   This process may be as simple as a single database access or it        may be a cascade process where multiple processes are employed        in sequence or in parallel to complete the required task.    -   “Located elsewhere” includes both databases and other processes        that must be located at a central location and databases and        other processes that are located at multiple different        locations. This inability to localize the database may be for        several reasons:        -   i. Proprietary control of the database that prevents release            into the field.        -   ii. The database won't fit on the capture device—in other            words, the data is required for the capture process but its            being local is prohibited by the capacity of the device.        -   iii. The database needs constant updating that is easier to            achieve if the database is kept in one place (i.e. the            database is dynamic on a time scale too short for reasonable            remote updating).        -   iv. The data access may be too process intensive for the            device (even if the data in it is not too large to fit).            This can happen when, for example, a manual stage must            intervene in the event of imperfect capture of the data.            This patent should cover the case where the “centralized”            part of the process is manual.        -   v. The database or other back-end process naturally occurs            in multiple locations (see, for example, the second half of            this patent) and hence cannot be localized completely at            all.        -   vi. It may simply be too expensive (due to licensing fees or            other considerations) to have a version of a database on            each in-field device.    -   b. In another embodiment, there is a unified capture process but        a diverse next phase of the process. This is most obvious where        data is captured at a single point, but that data will be used        in many different processes which may be located in multiple        locations, require multiple and scattered databases, or simply        have multiple different purposes. An example is provided below        entitled “LTL Trucking Example”.    -   c. Another example of this involves an invoice. The “field”        location is the point of receipt of a shipment of parts on the        loading dock of a company. The incoming invoice/bill of lading        is scanned by a in-field device where the image of the form is        captured and at least part of it recognized. On the invoice is        data needed by several disparate processes including        instructions on who gets the arriving package, how to update the        inventory control system to account for its contents, the        shipper, the billing information and so on.    -   d. The databases, in both cases, may be accessible OTA (Over the        Air) or by other link by the mobile/kiosk device and, say,        labels created at that point, or the information captured may be        passed on to other systems with no further involvement of the        capture device and no further connection (at least for some of        them) with the item being processed (the item doesn't need to go        to the station doing bill paying, for example)

Less than TruckLoad (LTL) Application

A typical example of utilizing mobile data capture as an input tomultiple backend processes is the LTL trucking example. A driver picksup a partial load (e.g. a pallet) for delivery. Using a mobile device,he captures an image of the entire bill of lading. This image then feedsinto the following processes, many of which could run either on thedevice or on a backend system:

-   -   1. Address recognition: delivery destination address is        recognized for route planning and optimization.    -   2. Billing information: delivery data (package count, size,        weight, etc.) is combined with destination information (if        necessary) to initiate the billing process for transportation        services, expediting revenue acceptance.    -   3. Content identification sticker: delivery content information        is transmitted to an inventory tracking database to update        availability of transported cargo (i.e. no longer available at        site A, available at site B on date of delivery).    -   4. Legal/archival: an image of the bill of lading can be        archived. If necessary, this image (including things like        shipper signature, hand-written delivery instructions, etc.) can        be made available in the event of legal issues.    -   5. Delivery notification: allow or expedite recipient        notification of expected delivery date/time.

Courier, Express, and Postal Applications

In some embodiments, products may be provided to support the industrialmobile recognition markets. These markets include familiar mail andparcel delivery lines of business but also new areas including formsrecognition and revenue acceleration capabilties. Existing softwareproducts, for example recognition products and related databases, may beported to mobile devices and Over The Air (OTA) configurations. In themobile software, the recognition systems may expose webserviceinterfaces. Mobile line-of-business (LOB) application providers canaccess recognition capabilties either native on the mobile deviceoperating system or OTA transparently depending on system configuration.

The mobile recognition software, and associated databases (for example,a “database of valid results”—further described below)—will producetechnology that enable mobile devices (computers, laptops, handhelds,smartphones, etc.) to read and recognize text and image informationcollected from on board imaging systems. In one application, a proposedproduct suite will provide value to mobile LOB applications by readingand validating address and forms information. In many cases thesefeatures will reduce the cost of data entry time and errors. In othercases, these capabilties will accelerate the collection of revenue byrecognising, recording and transmitting delivery or pick up confirmationinformation.

TABLE Representative Problems and Solutions The Problem of UAA letterand parcel addressing Affects This affects the letter or parcel deliveryagency where costs are increased and/or revenue delayed due to faultyinformation The impact of which The impact of the problem is lost ordelayed revenue and/or is increased cost due to unanticipated additionalhandling or processing of articles. A successful solution A solutionwould be the automated recognition and validation of would be addressinformation at the point of induction and delivery. The Problem of Billof lading recognition and confirmation of delivery Affects This affectsthe cargo delivery agency. The impact of which The impact of the problemis delayed revenue and/or increased cost is due to time lapse betweencourier execution or receiver confirmation and data entry to billingsystem A successful solution A solution would be the automatedrecognition and validation of bill would be of lading information andimaging of receiver acknowledgement (signature). This information andpotentially GPS coordinate data on point of delivery would betransmitted OTA to back office billing systems for immediate invoicingwhere this process would previously be delayed by hours or days whileinformation traveled back to office overland. The Problem of Inventorymanagement Affects Supply chain management The impact of which increasedcost of inventory reconciliation and management or lost is revenue Asuccessful solution A forms recognition solution coupling textrecognition, barcode and would be potentially RFID and GPS data toquantify supply inventory. A mobilized recognition system could be usedto identify and quantify supplies and their location within a supplychain.

FIG. 2 is a simplified block diagram of an illustrative mobile softwarecomponent stack. FIG. 3 depicts a sample arrangement of the mobilizedand fixed deployment components of a system consistent with the presentdisclosure, in which a mobile or kiosk device includes a software stackof the type illustrated in FIG. 2. These components include the OCR andDirectory in a native implementation installed on the mobile devices,but also an OTA service configuration.

This architecture provides a flexibility where native and OTA hostedprocesses can be mixed to meet a range of solution constraints. Examplesof these constraints include geographic regions where wireless networkconnectivity is limited. In this case, native application functionalityis desired since OTA sited systems will be unreachable. Conversely, OTAconfigurations are desirable where network availability is high and/ormobile device capabilities are constrained. In these cases, a thinclient requiring minimal resources could be installed on the mobilecomputer which accesses recognition and validation features over thewireless data network.

FIG. 4 is a simplified example of a flow diagram illustrating operationof a mobile or in-field device. Here, following image capture (on themobile device), the recognition system selects whether to use nativeresources (recognition software), or employ recognition services on aremote server. However, this is preferably not an either- or (mutuallyexclusive) determination. Rather, as discussed later, the mobile devicein some embodiments may use no remote services, or some of them, oressentially all of them, depending on the circumstances and the need.For example, local (native) recognition may be sufficient for manyimages, but remote server assistance (a more robust recognition process)may be needed for some other images.

FIG. 5 is a flow diagram that illustrates the concept of the mobiledevice conducting recognition of digital image data using nativeresources, over a WiFi link, or via a wireless telecom networkconnection to a recognition system interface on a remote server. Anyavailable communications resource may be used.

Examples User Environment

The user environment of the mobile unit preferably includes integratedline of business applications in the shipping, supply chain management,inventory management and related industries. It is envisioned thatmobile machine based recognition and data validation technologies willimprove cost control and revenue acceleration for these establishedindustries.

In one embodiment, a mobile unit in accordance with the disclosurecomprises a ruggedized mobile computer. For example, such devices arecommercially available from Intermec Corporation, including withoutlimitation the following models:

-   -   CN3—Windows mobile v5.0 and v6.1    -   CN4—Windows mobile v6.1    -   CN50—small and large memory configuration, Windows mobile v 6.1        (v7 IIEGH)

Functional Objectives

Preferably the recognition software mobile application stack will beaccessible to use LOB application developers via the mobile hardwareplatform IDL or API's. In one example, RAF Technology's Argosy Post®Mobile API will be exposed via a data collection resource kit.

Port OCR and Directory

In an embodiment, RAF Technology, Inc.'s existing line of industryleading Argosy Post OCR and SmartMatch Directory products may be portedto Windows Mobile or some other mobile environment.

Integrate on-Board Systems

In some embodiments, the mobile software environment may integrate withvarious onboard interfaces including scanners, cameras, framers, pushbuttons, etc. Thus, for example, an OCR application receives digitalimage data from an on-board (or connected) digital camera. Preferably,an interface layer and components virtualize the OCR and directorycomponents.

“Fast Scan” Option

In some embodiments, a mobile device with a scanner (on board orconnected) may be configured to scan one image after another as fast asthe scanner works. The mobile device recognizes what it can, and queuesup the remaining images for either rescan or manual processing. In anembodiment, the flow of image data and recognition results may bemanaged using a queue or buffer. Thus a mobile device for OCR may appearto the user to be as fast as say, a barcode scanner, when in fact it isnot.

E-citation Applications

Currently many municipalities are experiencing budget deficits and arefacing pressure to maximize fund collections by issuing fines formoving, parking and local ordinance violations. In addition, bothgovernment and private companies want to control the flow of vehicles inmany applications, including automatic toll collection, structureaccess, and vehicle tracing and tracking.

For motorcycle, bicycle, and foot patrol law enforcement officers, eachtime they leave their vehicle puts these field workers at a higher risk.Each minute spent on the side of the road increases exposure to a lawviolator or to the risk of being hit by traffic. The kind of interactionthat takes place between the police and possible violators is of threekinds: determining who the policeman is dealing with, determiningwhether there is a possible infraction, and then if there is, dealingwith the driver.

Our mobile device is mounted on the patrol car or motor cycle (it can behooked into the camera on the front of patrol cars or motorcycle) orhand-held for, for example, foot patrolmen) and so aimed that it findsand reads the license plate of any car that comes within its sight.Through its connection to a database it determines whether the car is ofinterest (or the policeman assert interest because, for example, the carwas speeding) and if it is of interest, provides the proper informationto the policeman, which can include but is not limited to what theinfraction is, who is the owner of record, what other information isavailable about the owner, any safety concerns, and so on. Our systemthus allows two of the three forms of interaction to be dealt with whilethe patrolman is still in his vehicle, thus reducing danger andinteraction time. In addition, the system that includes our mobiletechnology can provide considerable information to the policeman onpotential drivers, enabling him to take appropriate precautions inapproaching the vehicle.

Beyond that, it may provide two additional pieces of information: it mayindicate the vehicle is not of interest, thus saving the time (andreducing the risk) of the patrolman interacting with the driver and itmay indicate that a vehicle that comes within view of the camera is ofinterest even though the attention of the policeman was not specificallydirected at that vehicle. This, of course, is particularly relevant tocar- or motorcycle-mounted devices that read whatever license platesthey seen.

This ability to enhance the “attention” of the patrolman is one of theenhancements our mobile technology makes possible since without 1)finding the license plate, 2) reading the license plate, and 3)connecting to back-end databases (all of which our system does) requiredthe policeman to first determine he should be interested in the vehicleand then enter all the information into the system himself.

In addition to ameliorating safety concerns, allowing early dismissal ofpossible interactions, and bringing otherwise-unnoticed vehicles to theattention of authorities, the mobile system makes possible far moreaccurate data capture in the even contact is made with the vehicle andits driver. Under most current situations, the policeman fills out acitation by hand (even in the most automated systems he still manuallyenters the information into the system) and then, later, someone (whomay or may not be the original policeman) manually reenters that datainto the electronic system.

Data entry errors are inherent with pen/paper citations despite anofficer's best effort to reduce mistakes such as incomplete, transposed,or incorrect information. Compounding the issue further, paper citationsintroduce additional errors during back-office processing, increasingthe risk of citation dismissals.

Our solution to this problem automates the citation process by usingmobile computers running sophisticated mobile data extraction andverification software, including connection to databases and otherback-end systems and an in-car printer, enabling the citation to beissued in exactly the same form in which the system holds theinformation. The effective e-Citation system we propose cuts the time toissue citations dramatically, reduces the need for many interactionswith the driver, enables vehicles not noticed by the policeman to beexamined automatically, and provides the officer with information on thevehicle and its potential drivers that may enhance his safety. Itautomatically captures critical vehicle and license information usingautomatic identification and data capture technology such as opticalcharacter recognition (OCR) and real-time database access, aggregatesinformation such as location, time, driver's license number, VIN, andlicense plate, associates that information with data obtained from adatabase (associated this time with the back-end system), and takes theaction required by the system of which our device is a part, such asprinting a citation, allowing vehicle access, and so on.

The benefit of embedding OCR technology on a mobile computer is thatallows an officer to scan a vehicle license plate and acquireinformation on the vehicle (and presumptive driver) without makingcontact or even getting out of the vehicle. It also provides the abilityto read more than just the license plate, including vehicleidentification number and the violator's driver's license and associatethose items in a database, use them to obtain additional information onthe violator or the vehicle, and so on. Once this information isautomatically captured & verified, real-time information can be providedto an officer which includes notification of outstanding arrestwarrants, identification of a stolen vehicle, or falsified license andvehicle owner information. Backup information can be simultaneouslyprovided to headquarters and to other patrol cars nearby, in the eventof trouble.

All this information can be quickly collected by a handheld orvehicle-mounted mobile computer which leaves the officers other handfree to perform additional critical tasks (which may involve holding hisweapon). All of the above is referenced to an automobile, but our systemcan be used for trucks, motorcycles and other road vehicles as well asboats and other means of transportation.

Within view of this patent is the ability to use a mobile or kiosk-baseddevice to capture identifying information for travelers for the benefitof TSA or other authorities. Right now, when you as a traveler presentTSA with your driver's license, all the TSA agent really knows is thathe has a piece of plastic with your picture on it that fluoresces. Wepresent a hand-held device that detects the fluorescence and alsocaptures all the information on the license whether photographic,printed, barcoded, or in a magnetic strip, sending that information tolocal or remote databases for confirmation that the picture goes withthe other data, that the person is allowed to fly, that there is noother reason to detain them, and a myriad of other purposes. Once again,the flow of the traveler is pre-determined by the way security andairports are run. We inject technology into existing flows withoutappreciably modifying those flows but enabling earlier, better, cheaper,or safer data capture and further processing of the item or person.

Technology Flow

In one example, an image of the license plate is captured by a mobiledevice, video camera in police car, camera at the entry point intosecure facility, etc. An OCR application recognizes the characters onthe license plate, driver's license, VIN number and so on. The OCRresults are looked up in one or more existing databases—list of licenseplates issued by a state, list of stolen vehicles, list of vehiclesallowed access into a secure facility, etc. —and the lookup results aredisplayed along with (if necessary or appropriate) any informationavailable on the vehicle or presumptive driver. In the case of a trafficstop, an image of the driver's license can be captured and OCR performedto induct the license into the system. The OCR results are looked up inone or more existing databases—licensed drivers within a state, list ofpeople with outstanding warrants, etc. —and the lookup results retrievedand displayed. The information collected and collated by the mobiledevice can be stored in yet another database. Any of the accesseddatabases can be local to the mobile device or on a central server(accessed via a mobile phone, radio, WiFi network or any other method).

Many applications such as the one discussed here will also allow manualentry of the data for those cases where the license plate etc. might beobscured, in too dim light, or otherwise not able to be read by themobile device. All the rest of the system will function as described.

Remote Deposit Capture (RDC) for Checks Applications

According to a 2011 AlixPartners study, a high level of mobile RDC checkmigration is expected by 2016. 2.1 billion checks are projected tomigrate to mobile RDC from other channels, with mobile RDC adoptersdepositing 73% of their paper checks via mobile RDC. For manybusinesses, particularly in direct store delivery, customers paying bycheck account to 20% or more of their daily customer transactions. Beingable to capture the information on those checks and process themdirectly in the normal course of a transaction (rather than later at abank, for example) is a major improvement given by our system'scapabilities.

Given the ongoing demand to improve a corporation's cash flow,substantial benefits can be realized by using a Remote Deposit Capturesolution in a corporation as both the remittance processing andfinancial transaction processing platform. “Check 21” legislation andtechnology enhancements allow for the convergence of these traditionallyseparate functions (Remittance Processing & Treasury Deposit Functions).The Check 21 federal law allows checks to be cleared off of acopy—including a digital electronic copy—of the original check.

Using Optical Character recognition software (OCR) operating locally ona mobile device can substantially reduce the number of keystrokesrequired for entering both the legal and courtesy amounts and forcapturing the personal information on the check such as name, address,bank routing number, bank account number, and check number.

Enhancing the service through the use of intelligent character anddocument recognition (ICR) can further automate the process byautomatically reading data on control documents such as invoices orbills of lading and intelligently comparing the information so capturedfor use within some back-end system.

Our system goes beyond just capturing, say, the courtesy amount on acheck (the numbers usually in a box). We extend the capture andprocessing capability to automate image and data capture of non-checkitems such as payment coupons, purchase orders or invoices as part of asingle capture act. In addition we capture and integrate personalinformation such as name, address, bank account number and so on fromthe check. Beyond automating the capture of information, the solutionscan produce file extracts to facilitate electronic consolidation ofreceivables data—thus eliminating the requirement to transport thesedocuments to a central site for processing. This is an example of usingthe capability of on-site capture to improve the workflow of anorganization (more about which later). Providing technology tofield-process and dispose of these items is a major benefit of ourinvention.

Technology Flow

An image of the document (check, coupon, invoice, etc.) is captured by amobile or Point of Sale (POS) device. An OCR/ICR applicationautomatically detects the document type and recognizes the appropriateinformation (e.g. check MICR line and amount, coupon value, or invoiceline items). The application transmits the image of the document andrecognition results to a backend system. Once the back-end systemacknowledges data receipt and induction, the paper document can then bedestroyed. All captured information is integrated and cross-checked andthe results sent to real-time and archival systems for appropriate use.

Intelligent Embedded Devices Applications

There are a great many places where workflows today transportinformation that could be used elsewhere or that could be providedearlier so as to enable better use of the information, but where thisinformation is not captured because it is not sufficiently valuable tointerrupt the process flow to acquire it. The mobile capability of theour system means that it can be embedded in objects that already handledata and in being embedded greatly enhance the data that can be capturedfrom the item and what can then be done with it.

Next I will use the example of an intelligent copier or fax machine, butit is intended that any ability to take data capture, database access,and intelligent back-end connectivity to the field for use in analready-existing processes and workflows is implied.

Examples above dealt with the case where the item to be captured was avehicle license, driver's license, meter, or check or supportingdocument. In those examples the item read was generally not specificallya “document” and the reason for capturing it often had nothing to dowith the item itself but was intended to give insight into somethingelse: the advisability of letting a traveler on an airplane, whether aparticular vehicle should be allowed into a parking structure, whether avehicle was stolen or its presumptive driver wanted for criminalactivity, how much electricity a customer is using.

This section addresses a more “office” or “warehouse” type ofenvironment where the items read are somewhat more “document” like. Theidea, however, of injecting capture technology into an already-existingflow to enable more to be done with that flow or that information,remains.

A fax machine may be used to transmit the image of an order form to abusiness. An intelligent fax machine with our embedded technology cancapture the information on that form, enter the results into a SAPsystem or even determine to whom it should be faxed. It could email theinformation to the intended recipient and just send the original imageas backup, for example. Incoming documents can be captured upon openingthe envelope and the system determine what to do with themautomatically, whether for routing to the appropriate person, filing,destroying, or placing an order or filing a complaint.

A further example of this consists of what to do with a package thatcomes into a mail room or to a loading dock. In the mail room, oursystem can capture information on or associated with the item (therecipient's address or mail stop for an incoming package, for example).But rather than just telling the mail room workers where to take thepackage—useful in its own right—it can also check a database of expectedreceipts (after reading the return address or some serial number or barcode on the package) and send the package not to the nominal addresseebut to where it is actually needed in the corporate work flow. It canalso highlight suspicious packages that do not appear to conform tostandard items received by the enterprise.

In the warehouse example, identifying data on the package can becaptured, paired with a previous order and an incoming invoice, all thatdata entered into an internal tracking system and the warehouse workertold which shelf on which to place the package—all without any moreintervention that using the mobile device to scan the item andassociated documentation.

Technology Flow

In each of these cases (indeed, in many of the cases covered in thispaper), there is an existing flow of people, automobiles, packages,documents, and so on. In this particular case an item is going throughthe workflow for one purpose—receipt at the loading dock, faxing to arecipient, receipt in the mail room—and using our in-the-field datacapture and processing capability, additional information can becaptured, compared with many different kinds of databases, and the itemor information about the item routed appropriately and automatically.

Each approach outlined here has a similar flow, so the case of loadingdock receipt is enough to show the technology flow. A package arrives onthe loading dock with associated paperwork. Rather than routing thepackage one place and each document someplace else, all are scanned withan embodiment of our system. The package enters into inventory control,a database is searched for where the contents of the package are to bestored, the proper people within the company are notified, the invoiceis sent to Payments, and everything else now knowable about the itemsent to the appropriate person immediately upon receipt. Our capabilityis to capture data, recognize it, contact one set of databases todetermine what it should say, aggregate information from multiple items(e.g. package and billing invoice), contact additional databases forinformation on what to do with the item and associated data, and provideall this information to the appropriate people—all without materiallychanging the flow of the package or its associated information except tomake the whole flow more immediate: at the point of first contact, moreaccurate, and more efficient.

Workflow Optimization Applications

In the proceeding we have stressed that our system enables in-the-fieldcapture of information in a way that does not interfere with the naturalflow of the item but that enables considerably more to be doneconsiderably earlier. This section notes one major thing that “can bedone” with the information whose capture our system makes possible.

We have looked extensively at using our system to provide an entity withthe information necessary to more efficiently transport an item to itsfinal destination. We hinted at this capability in the loading dockexample earlier. In this section we look more explicitly at thecapabilities provided by our system for optimizing a transshipmentoperation such as FedEx. Although what follows will concentrate on oneparticular application (we are engaged in sales efforts for the mobiledevice with FedEx at the current time), it is meant to apply broadly.

FedEx collects parcels, packages, and overnight letters from companiesand individuals. Approximately 80% of the time the destination andtracking information about that item is already in the FedEx system,since it was so entered by the shipper. About 20% of the time (more insome places, less in others), however, that information is not entered.Two common causes of this are small enterprises or individuals who arenot electronically connected to the FedEx system, and enterprises of allsize that have “just one more” item to hand the person making thepickup.

Today, all items (those already inducted into the FedEx system and thosenot) are shipped to a centralized point where the items that have notbeen inducted have their information manually entered into the FedExsystem. This is the first time the electronic FedEx system has seen theitem. In addition, for those items already in the system, when they arescanned at the aggregation point is often the first time the FedExsystem knows an expected item has actually been physically presented tothem.

Essentially, therefore, the system knows nothing about 20% of the itemsarriving at the aggregation point and has only partial information aboutthe remaining 80%. In addition to this, approximately 5% of the dataalready entered in the system is wrong (and a higher percentage of theitems that haven't been entered). The error is very often in thedelivery address, which means the shipper has to be called or the itemreturned for better addressing.

With our system, the driver can confirm all delivery addresses at thepoint of pickup and electronically induct all packages into the FedExsystem at the point of first contact. This, in general, gives FedEx anadditional half day to figure out what to do with the item. Because allthe information is captured, including item weight and type (e.g.letter, parcel, package), truck and airplane use can now be scheduled inadvance since, because of the RAF system, how much is going where isknown hours before it arrives at the aggregation point. In addition tothe above, the RAF system can allow dimensioning of the package so thatits physical size can be known to the system prior to arrival at theaggregation facility. This additional information further narrows theuncertainty of how many transportation vehicles will be needed to gowhere.

Technology Flow (described in the main text immediately above).

First Example Systems, Methods, and Apparatuses

In an example, a system is provided. The system may include a serverequipped for wireless data communication with a remote mobile unit; anda mobile unit equipped for wireless data communication with a server;the mobile unit including—an image capture unit to provide a digitalimage of a parcel; and a digital processor arranged for executingsoftware code stored in the mobile unit responsive to the digital image;the stored software code including—a customer application layer, arecognition system interface component, and a directory adaptercomponent configured to provide directory services to the recognitionsystem interface component to verify, complete or correct preliminarydestination address data.

In an example, the system includes a native address data extractioncomponent stored in the mobile unit; and wherein the recognition systeminterface component is configured to interact with the native addressdata extraction component to generate preliminary address data; and therecognition system interface component is configured to interact withthe directory adapter to verify or correct the preliminary address dataand return verified or corrected address data to the customerapplication layer or user interface.

In an example of the system, the recognition system interface componentincludes an interface for wireless communication with the server, andthe server is configured to provide remote recognition services to themobile unit via the recognition system interface component. The remoterecognition services available in the server may include at least one ofmachine print and handwritten postal address recognition services. Theremote recognition services available in the server include formsrecognition services.

In an example of the system, the digital image comprises a bar code onthe parcel or mail piece.

In an example of the system, the mobile unit further includes a localdirectory database [Smart Match-i] configured to interact with thedirectory adapter component to provide directory services.

In an example of the system, the directory adapter component includes aninterface for wireless communication with the server, and the server isconfigured to provide remote services to the mobile unit via thedirectory adapter component. The remote directory services available inthe server may include forms recognition services. The remoterecognition services available in the server may include postaldirectory services. The remote recognition services available in theserver may include postal address cleansing or NCOA services.

In an example of the system, the mobile unit further includes a localdirectory database configured to interact with the directory adaptercomponent to provide directory services; and further includes a nativeaddress data extraction component stored in the mobile unit; and whereinthe recognition system interface component is configured to interactwith the native address data extraction component to generatepreliminary address data; and the recognition system interface componentis further configured to interact with the directory adapter to verifyor correct the preliminary address data and return verified or correctedaddress data to the customer application layer or user interface.

In an example, a server is provided. The server includes a processor andstores software components in memory for execution in the processor, thestored software components including: a communication component forwireless data communication with a remote mobile unit; a recognitioncomponent to provide remote address recognition services to the mobileunit; and a directory services component to provide remote directoryservices to the mobile unit.

In an example of the server, the address recognition services includemachine print address recognition services. The address recognitionservices may include hand written address recognition services. Theaddress recognition services may include other recognition services.

In an example of the server, the remote directory services includepostal directory and address cleansing services.

In another example, a method is provided. The method includes in ahand-held mobile unit, capturing a digital image of a portion of aparcel or mail piece; in the mobile unit, processing the captureddigital image to extract preliminary address data; in the mobile unit,processing the preliminary address data to form verified or correctedaddress data; and associating the parcel or mail piece with the verifiedor corrected address data prior to submitting the parcel or mail pieceto an automated routing system, thereby insuring that correctdestination data is associated with the parcel or mail piece beforeattempting automated routing.

In an example, the method includes wirelessly communicating with aremote server for processing the captured digital image to extractpreliminary address data.

In an example, the method includes wirelessly communicating with aremote server for processing the preliminary address data to formverified or corrected address data.

In an example, the method includes wirelessly communicating with aremote server for downloading GPS location data associated with theverified or corrected address data.

In an example, the method includes printing the corrected address dataon a new label and adhering the new label to the parcel or mail piece.

Some of the above numbered examples in paragraphs 0045-0060 are narroweror more specific than the full scope of the present disclosure. Forexample, the present disclosure applies to virtually ANY automatedrecognition process, not merely address recognition. Some examples ofother recognition processes, say recognizing passports or field servicetags, are identified in the “Second example systems, methods, andapparatuses” below.

In general, many recognition processes require a corresponding databaseof allowed (or valid) results. Such a database may be part of a back-endsystem. A recognition process may query the back-end system, for examplesending it incomplete or “proposed” recognition data, and receive backmore complete or corrected recognition results. It also may receive dataassociated with the recognition results. As discussed above, a postaladdress “directory” is just one example of a database of allowed (orvalid) results. Other examples are shown in the Second example systems,methods, and apparatuses below, but these too are merely illustrativeand not intended to be limiting.

In other embodiments, an item has an RFID tag and there exists adatabase connecting that ID tag to a set of operations or procedures todo with the item. This should work both for native and over the airprocessing. Information may be captured (e.g. from a document), andcombined with the information already in the RFID database. Theresulting information may be used modify the downstream processing ofthe item. This can also be done with tracking barcodes on the item aswell as with RFID chips or any other on-object identifier of the object.

There are two main implementations of the claimed system, but these arenot exclusive or exhaustive. One has native processing for thecomponents (e.g. machine print, handwriting, directory), and the otherhas over the air (OTA) connection to a server where some of thoseprocesses are carried out. Preferably, there is a continuum fromeverything is native to the device and there is no connection to theoutside world (read an address, print a routing barcode with therecognition and directory both native and the printer for the routingbarcode label connected physically to the mobile device), all the way towhere the mobile device captures the image and does nothing else, withall the components resident on the server. Our concept covers the wholecontinuum, and it is important that there IS a continuum—it isn't justnative or over the air (OTA) for the whole thing. Various components canbe native and others accessible on the server. In this broader light, asecond example of systems, methods, and apparatuses follows. Again,these are not intended to be limiting, but they provide further examplesof embodiments and features of the present disclosure.

Second Example Systems, Methods, and Apparatuses

In an example, a system is provided. The system includes a portable,in-field unit including: an RFID tag reader to acquire an ID tagidentifier from an RFID tag located in or on a physical item positionedwithin functional range of the in-field unit RFID tag reader; a digitalprocessor arranged for executing software code stored in the in-fieldunit responsive to the acquired ID tag identifier, the stored softwarecode including—a customer application layer; and a database adaptercomponent configured to provide database services to the processor;wherein the database services include accessing a stored database toacquire stored data associated with the acquired ID tag identifier.

In an example, the stored database is stored in the in-field unit.

In an example, the stored database is accessed via wirelesscommunication with a remote server.

In an example, the stored database contains a set of operations orprocedures associated with or indexed to each ID tag identifier.

In an example, the software code executable on the in-field unit isoperable to return to the customer application layer the stored set ofoperations associated with the acquired ID tag identifier.

In an example, the software code executable on the in-field unit isoperable to mark (label) the physical item responsive to the stored setof operations associated with the acquired ID tag identifier.

In an example, the software code executable on the in-field unit isoperable to electronically send a message to a predetermined recipientresponsive to the ID tag identifier.

In an example, a method is provided. The method includes capturing adigital image in an in-field device of an optical identifier visible ona physical item positioned proximate to the in-field device; recognizinginformation in the captured digital image to determine a recognitionresult; and transmitting the recognition result to a backend systemremote from the in-field device, wherein the backend system isconfigured to take a predetermined action or provide data responsive toreceiving the recognition result.

In an example, the recognizing step is carried out independently in thein-field device.

In an example, the recognizing step is carried out in the in-fielddevice with support from a remote server. The method may include sendingpreliminary recognition data from the in-field device to the remoteserver, and receiving recognition results from the remote server. Themethod may include accessing a database of valid results in support ofthe recognition step, the database of valid results accessible to eitherthe in-field device or the remote server.

In an example, the recognizing step comprises sending the captureddigital image to a remote server, and receiving a recognition resultfrom the remote server.

In an example, the backend system is coupled to the in-field device.

In an example, the backend system is coupled to the remote server.

In an example, said recognizing step utilizes at least one selectedrecognition software component that is native in the in-field device,and also utilizes at least one other recognition software component thatis deployed on the remote server. The method may include selecting atleast one native recognition component when communication with theremote server is not available.

In any of the example methods, the recognizing step comprisesrecognizing identifier data from digital images of at least one of—mailpieces and packages, passports, drivers licenses, ID cards, vehiclelicense plates, part IDs, object IDs, field service tags, machinery IDs,and package IDs.

In any of the example methods, the backend system comprises a databaseof records that reflect at least one of—a terrorist watch list, list ofoutstanding arrest warrants, Amber alerts, list of traffic violations,license suspensions, postal system destination addresses, equipmentidentification and associated databases for field service, andallowed-access databases, for accessing a gate, door or other physicalaccess portal. In an example, the backend system transmits a messageresponsive to receiving the recognition result.

In an example, a method is provided. The method includes, in an in-fielddevice, capturing an identifier of a nearby physical object from anon-object identifier, wherein the identifier is associated with a recordin a predetermined database; in the in-field device, capturinginformation from a document; combining the captured information withexisting information in the said database record to form a result; andapplying the result to modify subsequent processing of the item. Theon-object identifier may comprise an RFID device. The on-objectidentifier may comprise a barcode.

In an example, an apparatus is provided. The apparatus may include animage capture unit to provide a digital image of an optical identifiervisible on a physical item positioned proximate to an in-field device;and a digital processor arranged for executing software code stored inthe in-field device, the stored software code configured to execute apredetermined action associated with the captured digital image.

In an example, the stored software code includes a recognition processfor recognizing information visible in the captured digital image, andfurther implements a linkage to a backend system remote from thein-field device to communicate results of the recognition process to thebackend system. The stored software code may implement a recognitionprocess for recognizing handwriting or machine print. The recognitionsoftware code may be configured for recognition of identifier data fromdigital images of at least one of—mail pieces and packages, passports,drivers licenses, ID cards, vehicle license plates, part IDs, objectIDs, field service tags, machinery IDs, package IDs. The backend systemmay return data to the in-field device or takes a predetermined actionresponsive to the results of the recognition process. The digitalprocessor may be configured to access a database of valid results foruse in support of the recognition process, to provide valid resultsbased on proposed results generated by the recognition process. Thedatabase of valid results may comprise records that reflect at least oneof—a terrorist watch list, list of outstanding arrest warrants, Amberalerts, list of traffic violations, license suspensions, postal systemdestination addresses, equipment identification and associated databasesfor field service, and allowed-access databases, for accessing a gate,door or other physical access portal.

The systems, methods, and apparatuses disclosed above may be applied toenable any or all of the following additional concepts.

A. Local correction of addresses: by having address recognition done atpoint of induction of package into the system (i.e. where it is pickedup from the shipper), you have the ability to determine it isundeliverable as addressed and to ask for a corrected address from thepeople who generated the address in the first place, saving the time ofhaving to send it back later (or calling them later) to get the correctaddress. Local mobile capture, described above, enables this capabilitywhich cannot be done with current devices.

B. Dynamic routing of packages. Induction of packages at point ofshipment (rather than at a hub) enables about ½ day extra time for thepackage to be in the system (the length of time for the pick-up truck tomake it back to the hub). This in turn enables the courier to schedulehis trucks/airplanes/camels better because he knows sooner what is goingwhere. This can be used with or without the next item, dimensioning. Ifused with dimensioning, enables not only the number of items going to adestination, but their size to be known a half-day earlier, enablingmuch better dynamic routing.

C. Dimensioning. A mobile device of the type disclosed above may beconfigured to determine the size and shape characteristics of a package(as well as capture what is on it). Today, dimensioning can be done onrectangular solids, determining the three primary dimensions.Dimensioning can consist of several things: the smallest rectangularsolid that can enclose an object (i.e. what size box would it fit in),the convex hull of the object (i.e. the smallest everywhere convex shapethat could contain the object) and, within limitations of visibility ofinternal voids, the actual volume and shape of the object includingholes.

Example: Consider a donut. A first dimensioning step would find therectangular solid box in which the donut would fit. The second wouldeffectively put flat planes across the hole and return that shape, whichwould be the size of the object if wrapped in wrapping paper. The thirdwould see the hole and return the exact size and shape of the donut.

In one embodiment, dimensioning may be done in concert with either thepackage induction (i.e. you capture the delivery address and also thepackage size/shape) or in concert with dynamic routing (as describedabove—you know how much room to allocate on the truck going to aparticular city half a day earlier) or both.

The system and apparatus described above may use dedicated processorsystems, micro controllers, programmable logic devices, microprocessors,or any combination thereof, to perform some or all of the operationsdescribed herein. Some of the operations described above may beimplemented in software and other operations may be implemented inhardware. One or more of the operations, processes, and/or methodsdescribed herein may be performed by an apparatus, a device, and/or asystem substantially similar to those as described herein and withreference to the illustrated figures.

A processing device may execute instructions or “code” stored in memory.The memory may store data as well. The processing device may include,but may not be limited to, an analog processor, a digital processor, amicroprocessor, a multi-core processor, a processor array, a networkprocessor, or the like. The processing device may be part of anintegrated control system or system manager, or may be provided as aportable electronic device configured to interface with a networkedsystem either locally or remotely via wireless transmission.

The processor memory may be integrated together with the processingdevice, for example RAM or FLASH memory disposed within an integratedcircuit microprocessor or the like. In other examples, the memory maycomprise an independent device, such as an external disk drive, astorage array, a portable FLASH key fob, or the like. The memory andprocessing device may be operatively coupled together, or incommunication with each other, for example by an I/O port, a networkconnection, or the like, and the processing device may read a filestored on the memory. Associated memory may be “read only” by design(ROM) by virtue of permission settings, or not. Other examples of memorymay include, but may not be limited to, WORM, EPROM, EEPROM, FLASH, orthe like, which may be implemented in solid state semiconductor devices.Other memories may comprise moving parts, such as a conventionalrotating disk drive. All such memories may be “machine-readable” and maybe readable by a processing device.

Operating instructions or commands may be implemented or embodied intangible forms of stored computer software (also known as “computerprogram” or “code”). Programs, or code, may be stored in a digitalmemory and may be read by the processing device. “Computer-readablestorage medium” (or alternatively, “machine-readable storage medium”)may include all of the foregoing types of memory, as well as newtechnologies of the future, as long as the memory may be capable ofstoring digital information in the nature of a computer program or otherdata, at least temporarily, and as long as the stored information may be“read” by an appropriate processing device. The term “computer-readable”may not be limited to the historical usage of “computer” to imply acomplete mainframe, mini-computer, desktop or even laptop computer.Rather, “computer-readable” may comprise storage medium that may bereadable by a processor, a processing device, or any computing system.Such media may be any available media that may be locally and/orremotely accessible by a computer or a processor, and may includevolatile and non-volatile media, and removable and non-removable media,or any combination thereof.

A program stored in a computer-readable storage medium may comprise acomputer program product. For example, a storage medium may be used as aconvenient means to store or transport a computer program. For the sakeof convenience, the operations may be described as variousinterconnected or coupled functional blocks or diagrams. However, theremay be cases where these functional blocks or diagrams may beequivalently aggregated into a single logic device, program or operationwith unclear boundaries.

One of skill in the art will recognize that the concepts taught hereincan be tailored to a particular application in many other ways. Inparticular, those skilled in the art will recognize that the illustratedexamples are but one of many alternative implementations that willbecome apparent upon reading this disclosure.

Although the specification may refer to “an”, “one”, “another”, or“some” example(s) in several locations, this does not necessarily meanthat each such reference is to the same example(s), or that the featureonly applies to a single example. It will be obvious to those havingskill in the art that many changes may be made to the details of theabove-described embodiments without departing from the underlyingprinciples of the invention. The scope of the present invention should,therefore, be determined only by the following claims.

1. An apparatus, comprising: an image capture unit to provide a digitalimage of an optical identifier visible on a physical item positionedproximate to an in-field device; and a digital processor arranged forexecuting software code stored in the in-field device, the storedsoftware code configured to execute a predetermined action associatedwith the captured digital image.
 2. The apparatus of claim 1, whereinthe stored software code includes a recognition process for recognizinginformation visible in the captured digital image, and furtherimplements a linkage to a backend system remote from the in-field deviceto communicate results of the recognition process to the backend system.3. The apparatus of claim 2, wherein the stored software code implementsa recognition process for recognizing handwriting or machine print. 4.The apparatus of claim 2, wherein the recognition software code isconfigured for recognition of identifier data from digital images of atleast one of—mail pieces and packages, passports, drivers licenses, IDcards, vehicle license plates, part IDs, object IDs, field service tags,machinery IDs, package IDs.
 5. The apparatus of claim 2, wherein thebackend system returns data to the in-field device or takes apredetermined action responsive to the results of the recognitionprocess.
 6. The apparatus of claim 2, wherein the digital processor isconfigured to access a database of valid results for use in support ofthe recognition process, to provide valid results based on proposedresults generated by the recognition process.
 7. The apparatus of claim5, wherein the database of valid results comprises records that reflectat least one of— a terrorist watch list, list of outstanding arrestwarrants, Amber alerts, list of traffic violations, license suspensions,postal system destination addresses, equipment identification andassociated databases for field service, and allowed-access databases,for accessing a gate, door or other physical access portal.
 8. A method,comprising: capturing a digital image in an in-field device of anoptical identifier visible on a physical item positioned proximate tothe in-field device; recognizing information in the captured digitalimage to determine a recognition result; and transmitting therecognition result to a backend system remote from the in-field device,wherein the backend system is configured to take a predetermined actionor provide data responsive to receiving the recognition result.
 9. Themethod of claim 8 wherein the recognizing step is carried outindependently in the in-field device utilizing a database stored in thein-field device.
 10. The method of claim 8 wherein the recognizing stepis carried out in the in-field device with wireless support from aremote server.
 11. The method of claim 10 including: sending preliminaryrecognition data from the in-field device to the remote server;receiving recognition results from the remote server responsive to thepreliminary recognition data; and then using the received recognitionresults to verify or correct the preliminary recognition data.
 12. Themethod of claim 10 including accessing a database of valid results insupport of the recognition step, the database of valid resultsaccessible to either the in-field device or the remote server.
 13. Themethod of claim 8 wherein the recognizing step comprises: attempting torecognize the information in the captured digital image locally in thein-field device; in the case that local recognition is not successful,sending the captured digital image over a wireless connection to aremote server; and receiving a recognition result from the remote serverresponsive to the captured digital image.
 14. The method of claim 8wherein the item positioned proximate to the in-field device is aparcel, and further comprising applying the recognition result from theremote server to complete or correct a destination address of the itembefore moving the item from a collection point in the field.
 15. Themethod of claim 8 wherein the backend system is coupled to the remoteserver.
 16. The method of claim 13 wherein said recognizing steputilizes at least one selected recognition software component that isnative in the in-field device, and also utilizes at least one otherrecognition software component that is deployed on the remote server.17. The method of claim 16 including selecting at least one nativerecognition component when communication with the remote server is notavailable.
 18. A method according to claim 17 wherein the recognizingstep comprises recognizing identifier data from digital images of atleast one of—mail pieces and packages, passports, drivers licenses, IDcards, vehicle license plates, part IDs, object IDs, field service tags,machinery IDs, and package IDs.
 19. A method according to claim 17wherein the backend system comprises a database of records that reflectat least one of— a terrorist watch list, list of outstanding arrestwarrants, Amber alerts, list of traffic violations, license suspensions,postal system destination addresses, equipment identification andassociated databases for field service, and allowed-access databases,for accessing a gate, door or other physical access portal.
 20. Themethod of claim 19 wherein the backend system transmits a messageresponsive to receiving the recognition result.
 21. A system comprising:a portable, in-field unit including: a tag reader to acquire an ID tagidentifier from a tag located in or on a physical item positioned withinfunctional range of the in-field unit tag reader; a digital processorarranged for executing software code stored in the in-field unitresponsive to the acquired ID tag identifier, the stored software codeincluding— a customer application layer; and a database adaptercomponent configured to provide database services to the processor;wherein the database services include accessing a stored database toacquire stored data associated with the acquired ID tag identifier. 22.The system according to claim 21 wherein the stored database is storedin the in-field unit.
 23. The system according to claim 21 wherein thestored database is accessed via wireless communication with a remoteserver.
 24. The system according to claim 21 wherein the stored databasecontains a set of operations or procedures associated with or indexed toeach ID tag identifier.
 25. The system according to claim 21 wherein thesoftware code executable on the in-field unit is operable to return tothe customer application layer the stored set of operations associatedwith the acquired ID tag identifier.
 26. The system according to claim21 wherein the software code executable on the in-field unit is operableto mark (label) the physical item responsive to the stored set ofoperations associated with the acquired ID tag identifier.
 27. Thesystem according to claim 21 wherein the software code executable on thein-field unit is operable to electronically send a message to apredetermined recipient responsive to the ID tag identifier.
 28. Amethod comprising: in an in-field device, capturing an identifier of anearby physical object from an on-object identifier, wherein theidentifier is associated with a record in a predetermined database; inthe in-field device, capturing information from a document; andcombining the captured information with existing information in the saiddatabase record to form a result; and applying the result to modifysubsequent processing of the item.
 29. The method of claim 28 whereinthe on-object identifier comprises an RFID device.
 30. The method ofclaim 28 wherein the on-object identifier comprises a barcode.
 31. Themethod of claim 28 wherein the document is one of a driver's license, apassport, or another document issued by a governmental agency to anindividual.
 32. The method of claim 28 wherein the document comprises abill of lading.